<h1 id="south-carolina-congressional-districts">2010 South Carolina
Congressional Districts</h1>
<h2 id="redistricting-requirements">Redistricting requirements</h2>
<p>In South Carolina, districts must:</p>
<ol type="1">
<li>be contiguous</li>
<li>have equal populations</li>
<li>be geographically compact</li>
<li>preserve county and municipality boundaries as much as possible</li>
<li>pass pre-clearance from the DOJ</li>
</ol>
<p>https://redistricting.scsenate.gov/Documents/RedistrictingGuidelinesAdopted041311.pdf
https://redistricting.schouse.gov/archives/2011/6334-1500-2011-Redistricting-Guidelines-(A0404871).pdf</p>
<h3 id="interpretation-of-requirements">Interpretation of
requirements</h3>
<p>We do not adhere to all criteria in the guidelines. We include the
following constraints:</p>
<ol type="1">
<li>We enforce a maximum population deviation of 0.5%.</li>
<li>We impose a hinge constraint on the Black Voting Age Population so
that it encourages districts with BVAP above 50%, but districts with
BVAP of 30% or less are not penalized as much. This ensures that
districts with high BVAP are able to elect their candidate of
choice.</li>
<li>We impose a municipality-split constraint to lower the number of
municipality splits.</li>
</ol>
<h2 id="data-sources">Data Sources</h2>
<p>Data for South Carolina comes from the ALARM Project’s <a
href="https://alarm-redist.github.io/posts/2021-08-10-census-2020/">2020
Redistricting Data Files</a>. &lt;- not sure what I should put for 2010
because I couldn’t find it in the ALARM website :(</p>
<h2 id="pre-processing-notes">Pre-processing Notes</h2>
<p>No manual pre-processing decisions were necessary.</p>
<h2 id="simulation-notes">Simulation Notes</h2>
<p>We sample 6,000 districting plans across two independent runs of the
SMC algorithm. We then remove all plans that do not contain any district
that has both a BVAP of over 30% and an average vote share that is more
Democratic than Republican. This removal occurs after verifying that
such plans comprise less than 1% of the 6,000 plans. We then thin the
sample down to exactly 5,000 plans. We also set the population tempering
to 0.01 to avoid bottlenecks.</p>
<h2 id="contents">Contents</h2>
<ul>
<li><code>SC_cd_2010_stats.csv</code> contains summary statistics on the
sampled redistricting plans</li>
<li><code>SC_cd_2010_plans.rds</code> is a compressed
<code>redist_plans</code> object, which contains the matrix of
precinct/block assignments and may be used for further analysis.</li>
<li><code>SC_cd_2010_map.rds</code> is a compressed
<code>redist_map</code> object, which contains the precinct/block
shapefile and demographic data.</li>
</ul>
<p>Both the <code>redist_plans</code> and <code>redist_map</code> object
are intended to be used with the <a
href="https://alarm-redist.github.io/redist/">redist package</a>.</p>
<h3 id="codebook-for-summary-statistics">Codebook for summary
statistics</h3>
<ul>
<li><code>draw</code>: unique identifier for each sample. Non-numeric
draw names are real-world plans, e.g., <code>cd_2010</code> for an
enacted 2010 plan.</li>
<li><code>district</code>: a district identifier. District numbers
roughly match those in the enacted plan, but the correspondence is not
perfect.</li>
<li><code>chain</code>: a number identifying the run of the
redistricting algorithm used to produce this draw. Used for diagnostic
purposes.</li>
<li><code>pop_overlap</code>: a number indicating the fraction of people
in this plan who reside in the same-numbered district in the enacted
plan.</li>
<li><code>total_pop</code>: the total population of each district.</li>
<li><code>total_vap</code>: the total voting-aged population of each
district.</li>
<li><code>pop_*</code>, <code>vap_*</code>: total (voting-aged)
population within racial and ethnic groups for each district. Variable
codes documented <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>plan_dev</code>: the maximum population deviation among
districts in the plan. Computed as
<code>max(abs(distr_pop - target_pop)/target_pop)</code>.</li>
<li><code>comp_edge</code>: compactness, as measured by the fraction of
internal edges kept. Higher values indicate more compactness.</li>
<li><code>comp_polsby</code>: compactness, as measured by the
Polsby-Popper score. Higher values indicate more compactness.</li>
<li><code>county_splits</code>: the number of counties which belong to
more than one district.</li>
<li><code>muni_splits</code>: the number of Census Designated Places
which belong to more than one district.</li>
<li><code>*_##_dem_*</code>, <code>*_##_rep_*</code>: vote counts for
statewide Democratic and Republican candidates in a certain election.
More information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>adv_##</code>, <code>arv_##</code>: average vote counts for
statewide Democratic and Republican candidates in a certain year. More
information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>ndv</code>, <code>nrv</code>: averages of the
<code>adv_##</code> and <code>arv_##</code> variables across all
available elections.</li>
<li><code>ndshare</code>: normal Democratic share, computed as
<code>ndv / (ndv + nrv)</code></li>
<li><code>e_dvs</code>: average Democratic vote share, computed as the
average of the Democratic vote share when first scored under each
statewide election.</li>
<li><code>pr_dem</code>: probability seat is represented by a Democrat;
calculated as the fraction of statewide elections under which the
district had a majority Democratic share.</li>
<li><code>e_dem</code>: expected number of Democratic seats for the
plan; equivalent to summing the <code>pr_dem</code> values across
districts</li>
<li><code>pbias</code>: partisan bias at 50% vote share, averaged across
all available elections. Positive values indicate Republican bias.</li>
<li><code>egap</code>: the efficiency gap, averaged across all available
elections. Positive values indicate Republican bias.</li>
</ul>
